Linear Arithmetic Satisfiability via Strategy Improvement

Authors: Azadeh Farzan, Zachary Kincaid

IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental Experimental results demonstrate that the proposed procedure is competitive with existing solvers. We evaluated SIMSAT on a suite of benchmarks drawn from SMT-LIB2 [Barrett et al., 2010] and Mjollnir [Monniaux, 2010].
Researcher Affiliation Academia Azadeh Farzan University of Toronto azadeh@cs.toronto.edu Zachary Kincaid Princeton University zkincaid@cs.princeton.edu
Pseudocode Yes Algorithm 1: Check if a strategy has a counter-strategy; Algorithm 2: Counter-strategy synthesis; Algorithm 3: Satisfiability modulo LRA
Open Source Code No The paper states, 'We have implemented Algorithm 3 in a prototype tool called SIMSAT,' but it does not provide a specific link or explicit statement about the source code being open or publicly available.
Open Datasets Yes We evaluated SIMSAT on a suite of benchmarks drawn from SMT-LIB2 [Barrett et al., 2010] and Mjollnir [Monniaux, 2010].
Dataset Splits No The paper discusses 'industrial benchmarks' and 'random benchmarks' for evaluation but does not specify any train, validation, or test dataset splits (e.g., percentages or sample counts).
Hardware Specification Yes The experimental evaluation was performed on a Linux machine with Intel Core i5 2.80GHz processors and 4GB of memory.
Software Dependencies No The paper mentions that the tool 'is implemented in OCaml and uses Z3 to solve ground formulas,' but it does not provide specific version numbers for OCaml or Z3.
Experiment Setup No The paper mentions a 'time limit was set to 300 seconds' for experiments but does not provide specific details on hyperparameters, model initialization, or other training configurations.